In nuclear medicine, images of internal structures or functions of the body are acquired by using one or more gamma cameras to detect radiation emitted by a radio-pharmaceutical that has been injected into the patient's body. A computer system controls the gamma cameras to acquire data and then processes the acquired data to generate the images. Nuclear medicine imaging techniques include single-photon emission computed tomography (SPECT) and positron emission tomography (PET). SPECT imaging is based on the detection of individual gamma rays emitted from the body, while PET imaging is based on the detection of gamma ray pairs emitted in coincidence in opposite directions due to electron-positron annihilations. Accordingly, PET imaging is sometimes referred to as "coincidence imaging". Nuclear medicine imaging systems, which are sometimes referred to as gamma camera systems, include dedicated SPECT systems, dedicated PET systems, and systems having dual PET/SPECT capability. Gamma camera systems with dual PET/SPECT capability are available from ADAC Laboratories of Milpitas, Calif.
Random coincidences are a factor that affects image quality in coincidence imaging. In coincidence imaging systems, coincidence events may be defined as two events observed by two detectors which occur within a relatively narrow time window. However, a certain fraction of event pairs detected within the time window are not the result of true coincidences (i.e., based on a single positron-electron annihilation) but are based on separate, unrelated annihilation events. Such detected event pairs are referred to as random coincidences, or "randoms". The misinterpretation of randoms as true coincidences produces inaccuracy in the imaging process and, therefore, degrades image quality.
A common approach to randoms correction is to provide a second coincidence timing circuit in parallel with the normal coincidence timing circuit. The second timing circuit includes a time delay on the trigger signal from one detector. The delay is made large enough so that no true coincidence events can be registered by the second timing circuit. Thus, any events which are detected in the second timing circuit can only result from random coincidences. The number and distribution of randoms detected by the parallel timing circuit are proportional to the number and distribution of randoms in the overall coincidence data. As a result, the randoms data can be essentially subtracted from the overall coincidence data.
This approach has a number of disadvantages. For example, it tends to involve a relatively complex hardware solution that adds to the cost and size of the gamma camera system. As radioactivity dosages increase to increase patient throughput, increasingly higher performance is demanded from the coincidence timing circuitry. In addition, since this solution is based on direct measurement of randoms, the effects of deadtime tend to complicate the measurement of randoms. Furthermore, because coincidences in general represent only a small fraction of the overall countrate, the acquired randoms data tends to be noisy.
Another approach to randoms correction is to form an estimate of randoms based upon a mathematical model. Because that approach is based upon only an estimate, however, it is inherently subject to inaccuracies. For example, such an estimate may not take into consideration the spatial variations in randoms. Hence, it is desirable to provide a technique for correcting for randoms in a medical imaging system which overcomes these and other disadvantages of the prior art.